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Abstract
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| Systems based on fixed-point arithmetic, when carefully designed, seem to behave as their infinite precision analogues. Most often, however, this is only a macroscopic impression: finite word-lengths inevitably approximate the reference behavior introducing quantization errors, and confine the macroscopic correspondence to a restricted range of input values. Understanding these differences is crucial to design optimized fixed-point implementations that will behave ?as expected? upon deployment. Thus, in this chapter, we survey the main approaches proposed in literature to model the impact of finite precision in fixed-point systems. In particular, we focus on the rounding errors introduced after reducing the number of least-significant bits in signals and coefficients during the so-called quantization process. | |
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International
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Si |
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Book Edition
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Book Publishing
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ISBN
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978-3-319-91733-7 |
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Series
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Book title
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Handbook of Signal Processing Systems |
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From page
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1063 |
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To page
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1101 |